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DSP Lab Experience.

DSP Lab Experience. The laboratory experience was amazing. Through this lab we learnt the practical applications of DSP. In this lab we performed various experiments on different types of filters like Butterworth, IIR, FIR. We had this lab once a week i.e on every tuesday. Every lab session we learnt something interesting. We performed 6 experiments on different types of filters. Every lab session was challenging and we had to apply the concepts taught to us by Talele sir during the lectures of this course. Whenever we had doubts, Sir helped us. His notes were extremely useful to perform the experiments. We also learnt about the various applications of DSP. his course was a learning experience. It was something all of us enjoyed. It's something all of us will cherish.

OAM and OSM.

The aim of this experiment was to perform filtering of long data sequence using overlap add method and overlap save method .The objective of this experiment is to write a function to implement overlap add and overlap save algorithm. The OAM and OSM methods divide the input signal into smaller lengths and filter output (FFT) of such smaller length signal is calculated. The overlapped portion is added in case of OAM and discarded in case of OSM. The resultant output is the output of the whole input signal.  The following are the conclusions drawn: 1) overlap add and overlap save are the two methods to find the output of digital FIR filters . 2) it consist of a long data sequence x(n) and a impulse response h(n) 3) the length of the output sequence is obtained by L=M+N-1 4) in overlap add method we get the convoluted output signal of the input with impulse response

Application of DSP

In this experiment, I reviewed a patent which describes digital signal processing filters to improve loudspeaker transient response.The field of invention relates to loudspeakers , specifically to loudspeaker system including digital signal systems. I learnt that to improve the loudspeaker response, a six step process is used.The process begins with identifying a substantially linear, time-invariant, and spatially-consistent loudspeaker mechanism causing transient response distortion. After characterizing the identified mechanism. Next step is to determine the characterized mechanism's two-port response. It is important to establish a target response for the characterized mechanism. This is followed by calculating an ideal filter to achieve the target response. This leads to designing a cost-reduced filter based on the ideal filter to thereby form a loudspeaker mechanism algorithm (LMA) filter.  Here is the patent link https:// patents .google.com/ pat...

DSP lab experience

DSP lab was a fun learning experience.We had our practicals on every Thursdays a We performed our experiments on DSP board and CCS compiler.Every thrusday we learnt something new. We got to know about the DSP board more as we performed experiments on it. CCS is a compiler which is used to run, debug,build projects, etc.The sensor boards are user friendly. This lab was instrumental in helping me understand the DSP concepts better. I was also the batch representative and I made sure that all chairs were arranged and the lights and fans were swtiched off when we left the lab. This lab taught me about the DSP processor and various sensors we can use with the DSP profproce. The theory of some of the experiments was known to us as we has Signals and systems in the previous semester. We used that knowledge while performing these experiments. The board is user friendly and great for learning.  The overall experience was really very good.

DFT and FFT

DFT is a tool to study the signal in frequency domain.On the day of lab session we understood the logic and wrote the code for DFT. We tested it for some inputs and verified the output by analytical method. DFT assumes input as periodic and gives  periodic output sequence ,energy of the signal in time and frequency domain is equal.If we do zero padding then number of points increases hence resolution and quality of spectrum increases while the approximation error ,frequency spacing decreases. We had to develop a program for FFT. During the lectures sir taught us how to find FFT for a 8 point sequence. So during pracs we had to complete FFT. Now as we knew the concept we were comfortable in building the algorithm. Implenting the flowgrapgh as it is in our code was difficult .The program was done , compiled and we got the results. It was observed that FFT is faster than DFT since it requires less no of real and complex additions and multiplications and also since FFT does the c...

Correlation

We performed correlation in which we had to find the autocorrelation and cross correlation. Correlation is used for checking the similarity between two signals The following conclusion are drawn on the basis of the experimentation and result analysis The autocorrelation of a signal attains maximum value at n=0 and this value is equal to the energy of the signal. The auto correlation of a signal is same as the autocorrelation of the delayed signal, i.e. x[n] o x[n]= x[n-k] o x[n-k]. Cross correlation of a signal with its delayed version (delayed by ‘k’ units) results in an advanced version of the autocorrelation of the signal itself, advanced by ‘k’ units. (i.e x[n] o x[n-k]=y[n+k]). Cross correlation of a signal with its scaled version (scaled by ‘k’ units) results in a scaled version of the autocorrelation of the signal itself, scaled by ‘k’ units. (i.e x[n] o (K)*x[n]=(2)*y[n]).

Convolution

Convolution is used to find out the output of an LTI system.If the response of the system to the impulse signal is known(h(t) or h(n)),then the response to any other input to the system can be found out by convolving the input signal with impulse response. Convolution is a very important process in analog as well as Digital signal,time signal or frequency  signal.it  gives us what will happen if two signals are shifted and mixed together. In this experiment, we found out the linear convolution of two signals and concluded that the output signal has the legth equal to one less than the sum of length of two input signals. Also, if both the input signals are casual then the LC output is also causal. While finding CC, the value of N is selected as the maximum of the two input signals. Zero padding is done in CC to make the signals with length equal. To find LC using CC, we select length of output signal as one less than the sum of length of two input signals. We made the...